tonyassi
/

vogue-fashion-collection-15

Image Classification

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tonyassi commited on Dec 28, 2023

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End of training

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README.md +15 -10
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README.md CHANGED Viewed

@@ -17,8 +17,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.4719
-- Accuracy: 0.8380
 ## Model description
@@ -46,17 +46,22 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 5
 ### Training results
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 6.1358        | 1.0   | 1094 | 6.1121          | 0.5762   |
-| 4.5926        | 2.0   | 2189 | 4.5302          | 0.7306   |
-| 3.386         | 3.0   | 3283 | 3.3786          | 0.7971   |
-| 2.7142        | 4.0   | 4378 | 2.7066          | 0.8231   |
-| 2.4032        | 5.0   | 5470 | 2.4719          | 0.8380   |
 ### Framework versions

 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.1795
+- Accuracy: 0.9454
 ## Model description
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
 ### Training results
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.6546        | 1.0   | 1094  | 1.8069          | 0.8558   |
+| 0.8991        | 2.0   | 2189  | 0.9520          | 0.8966   |
+| 0.589         | 3.0   | 3283  | 0.5906          | 0.9158   |
+| 0.4017        | 4.0   | 4378  | 0.4167          | 0.9273   |
+| 0.2594        | 5.0   | 5472  | 0.3189          | 0.9358   |
+| 0.308         | 6.0   | 6567  | 0.2758          | 0.9363   |
+| 0.2114        | 7.0   | 7661  | 0.2338          | 0.9419   |
+| 0.1439        | 8.0   | 8756  | 0.2131          | 0.9443   |
+| 0.1568        | 9.0   | 9850  | 0.1943          | 0.9454   |
+| 0.1388        | 10.0  | 10940 | 0.1795          | 0.9454   |
 ### Framework versions

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